{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Output/APPENDIX B MODELS.04-20-2021.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}22 Apr 2021, 21:08:51
{txt}
{com}. 
.    
.    
.       
. 
.    **** APPENDIX C: WEIBULL PROPORTIONAL HAZARD MODEL ESTIMATES OF CONFIRMATION DECAY ****
.  
.  
.  
.  
. 
.  
.  * OPEN UPDATED "CONFIRMATION DYNAMICS" DATABASE [08-13-2020] *
.  
. use "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Data/Confirmation Dynamics.Database.08-13-2020.FINAL.dta", replace
{txt}
{com}. 
. 
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. 
. 
. *** MODEL B.1: ESTIMATES FOR OVERALL CONFIRMATION DELAY [CONFIRMATION DATE - NOMINATION DATE] USING WEIBULL PH REGRESSION ****
. *drop _d _t _t0
. 
. ** STEP 1: ADD A CONSTANT OF 1 TO THE CONFIRMATION DURATION VARIABLE SO THAT IMMEDIATE CONFIRMATIONS ARE NOT CENSORED [CONFDURPLUS1 = confdur + 1] 
. gen confdurplus1 = confdur + 1
{txt}(273 missing values generated)

{com}. 
. ** STEP 2: SPECIFY NOMINATIONS THAT RESULT IN CONFIRMATIONS IN SAME CONGRESS [CONFIRMOBSERVED==0] AS 'FAILURES' WHEN SETTING THE DEPENDENT VARIABLE'S SURVIVAL FUNCTION **
. stset confdurplus1, failure(confirmobserved)

     {txt}failure event:  {res}confirmobserved != 0 & confirmobserved < .
{txt}obs. time interval:  {res}(0, confdurplus1]
{txt} exit on or before:  {res}failure

{txt}{hline 78}
{res}      1,345{txt}  total observations
{res}        273{txt}  event time missing (confdurplus1>=.)               PROBABLE ERROR
{hline 78}
{res}      1,072{txt}  observations remaining, representing
{res}      1,049{txt}  failures in single-record/single-failure data
{res}     75,421{txt}  total analysis time at risk and under observation
                                                at risk from t = {res}        0
                                     {txt}earliest observed entry t = {res}        0
                                          {txt}last observed exit t = {res}      922
{txt}
{com}. *
. ** STEP 3: ESTIMATE A WEIBULL HAZARD MODEL AND REPORT COEFFICIENTS IN  HAZARD RATIO FORM **
. streg filipresdistancelewiszb filipresdistlewiszbtoplev2  senpartydiffmedianlewiszb senpartydiffmedlewiszbtoplev2  senworkload senhearing excalendarcong ///
> senmajagencyideoloppose senmajagencyideolalign agencyindzb  agencyindzbtoplev2  soucountagency1  presappnom endsession newpresterm fvatreated  ///
> toplevel2 zloyalmedianzb zloyalmedianzbtoplev2 zmecompmedian zpecompmedian  gender minority admintermyr1  admintermyr2 admintermyr3 ///
> bush41 clinton bush43, distribution(weibull) vce(cluster sbagency) 

         {txt}failure _d:  {res}confirmobserved
   {txt}analysis time _t:  {res}confdurplus1

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1650.3441
{txt}Iteration 1:   log pseudolikelihood = {res}-1642.2607
{txt}Iteration 2:   log pseudolikelihood = {res}-1642.2605
{txt}Iteration 3:   log pseudolikelihood = {res}-1642.2605

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1642.2605}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1512.9735}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1444.5688}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1443.8418}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1443.8415}  
Iteration 5:{space 3}log pseudolikelihood = {res:-1443.8415}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}       1,013             {txt}Number of obs    =  {res}     1,013
{txt}No. of failures      = {res}         991
{txt}Time at risk         = {res}       70515
                                                {txt}Wald chi2({res}29{txt})    =  {res}    904.20
{txt}Log pseudolikelihood =   {res}-1443.8415             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 95:(Std. Err. adjusted for {res:50} clusters in sbagency)}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                           _t{col 31}{c |} Haz. Ratio{col 43}   Std. Err.{col 55}      z{col 63}   P>|z|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}filipresdistancelewiszb {c |}{col 31}{res}{space 2} 7.083465{col 43}{space 2} 12.10309{col 54}{space 1}    1.15{col 63}{space 3}0.252{col 71}{space 4} .2487993{col 84}{space 3} 201.6704
{txt}{space 3}filipresdistlewiszbtoplev2 {c |}{col 31}{res}{space 2} .4122351{col 43}{space 2} .2286559{col 54}{space 1}   -1.60{col 63}{space 3}0.110{col 71}{space 4} .1389972{col 84}{space 3} 1.222599
{txt}{space 4}senpartydiffmedianlewiszb {c |}{col 31}{res}{space 2} 8.97e-09{col 43}{space 2} 5.32e-08{col 54}{space 1}   -3.12{col 63}{space 3}0.002{col 71}{space 4} 8.01e-14{col 84}{space 3} .0010044
{txt}senpartydiffmedlewiszbtoplev2 {c |}{col 31}{res}{space 2} 103.7048{col 43}{space 2}  218.811{col 54}{space 1}    2.20{col 63}{space 3}0.028{col 71}{space 4} 1.658877{col 84}{space 3} 6483.115
{txt}{space 18}senworkload {c |}{col 31}{res}{space 2} .9982603{col 43}{space 2} .0006324{col 54}{space 1}   -2.75{col 63}{space 3}0.006{col 71}{space 4} .9970217{col 84}{space 3} .9995005
{txt}{space 19}senhearing {c |}{col 31}{res}{space 2} 1.001614{col 43}{space 2} .0005937{col 54}{space 1}    2.72{col 63}{space 3}0.007{col 71}{space 4} 1.000451{col 84}{space 3} 1.002779
{txt}{space 15}excalendarcong {c |}{col 31}{res}{space 2} .9999259{col 43}{space 2} .0000945{col 54}{space 1}   -0.78{col 63}{space 3}0.433{col 71}{space 4} .9997407{col 84}{space 3} 1.000111
{txt}{space 6}senmajagencyideoloppose {c |}{col 31}{res}{space 2} .9939712{col 43}{space 2} .1974878{col 54}{space 1}   -0.03{col 63}{space 3}0.976{col 71}{space 4} .6733676{col 84}{space 3}  1.46722
{txt}{space 7}senmajagencyideolalign {c |}{col 31}{res}{space 2} 1.025917{col 43}{space 2} .2107996{col 54}{space 1}    0.12{col 63}{space 3}0.901{col 71}{space 4} .6858235{col 84}{space 3} 1.534661
{txt}{space 18}agencyindzb {c |}{col 31}{res}{space 2} .8456403{col 43}{space 2} .0760892{col 54}{space 1}   -1.86{col 63}{space 3}0.062{col 71}{space 4} .7089181{col 84}{space 3} 1.008731
{txt}{space 11}agencyindzbtoplev2 {c |}{col 31}{res}{space 2} .9791693{col 43}{space 2} .1299608{col 54}{space 1}   -0.16{col 63}{space 3}0.874{col 71}{space 4} .7548864{col 84}{space 3} 1.270089
{txt}{space 14}soucountagency1 {c |}{col 31}{res}{space 2} 1.037755{col 43}{space 2} .0186457{col 54}{space 1}    2.06{col 63}{space 3}0.039{col 71}{space 4} 1.001846{col 84}{space 3}  1.07495
{txt}{space 19}presappnom {c |}{col 31}{res}{space 2} .9888522{col 43}{space 2} .0045583{col 54}{space 1}   -2.43{col 63}{space 3}0.015{col 71}{space 4} .9799584{col 84}{space 3} .9978267
{txt}{space 19}endsession {c |}{col 31}{res}{space 2} .6562263{col 43}{space 2} .1625091{col 54}{space 1}   -1.70{col 63}{space 3}0.089{col 71}{space 4} .4038875{col 84}{space 3}  1.06622
{txt}{space 18}newpresterm {c |}{col 31}{res}{space 2} 1.709578{col 43}{space 2} .1645768{col 54}{space 1}    5.57{col 63}{space 3}0.000{col 71}{space 4} 1.415617{col 84}{space 3} 2.064581
{txt}{space 19}fvatreated {c |}{col 31}{res}{space 2} 1.089731{col 43}{space 2} .1432071{col 54}{space 1}    0.65{col 63}{space 3}0.513{col 71}{space 4} .8422843{col 84}{space 3} 1.409873
{txt}{space 20}toplevel2 {c |}{col 31}{res}{space 2} .6545116{col 43}{space 2} .2058547{col 54}{space 1}   -1.35{col 63}{space 3}0.178{col 71}{space 4} .3533462{col 84}{space 3} 1.212367
{txt}{space 15}zloyalmedianzb {c |}{col 31}{res}{space 2} .8819146{col 43}{space 2} .0499903{col 54}{space 1}   -2.22{col 63}{space 3}0.027{col 71}{space 4} .7891819{col 84}{space 3} .9855438
{txt}{space 8}zloyalmedianzbtoplev2 {c |}{col 31}{res}{space 2} 1.612293{col 43}{space 2} .1609063{col 54}{space 1}    4.79{col 63}{space 3}0.000{col 71}{space 4}  1.32585{col 84}{space 3} 1.960621
{txt}{space 16}zmecompmedian {c |}{col 31}{res}{space 2} .9934413{col 43}{space 2} .0555713{col 54}{space 1}   -0.12{col 63}{space 3}0.906{col 71}{space 4}  .890282{col 84}{space 3} 1.108554
{txt}{space 16}zpecompmedian {c |}{col 31}{res}{space 2} .9439462{col 43}{space 2} .0492435{col 54}{space 1}   -1.11{col 63}{space 3}0.269{col 71}{space 4} .8522011{col 84}{space 3} 1.045568
{txt}{space 23}gender {c |}{col 31}{res}{space 2} 1.023471{col 43}{space 2} .0805496{col 54}{space 1}    0.29{col 63}{space 3}0.768{col 71}{space 4} .8771707{col 84}{space 3} 1.194173
{txt}{space 21}minority {c |}{col 31}{res}{space 2} .9408853{col 43}{space 2} .1009977{col 54}{space 1}   -0.57{col 63}{space 3}0.570{col 71}{space 4} .7623703{col 84}{space 3} 1.161201
{txt}{space 17}admintermyr1 {c |}{col 31}{res}{space 2} 1.634761{col 43}{space 2} .3568098{col 54}{space 1}    2.25{col 63}{space 3}0.024{col 71}{space 4} 1.065779{col 84}{space 3} 2.507501
{txt}{space 17}admintermyr2 {c |}{col 31}{res}{space 2} 1.471038{col 43}{space 2} .3519908{col 54}{space 1}    1.61{col 63}{space 3}0.107{col 71}{space 4} .9203391{col 84}{space 3} 2.351256
{txt}{space 17}admintermyr3 {c |}{col 31}{res}{space 2} 1.328192{col 43}{space 2} .2083086{col 54}{space 1}    1.81{col 63}{space 3}0.070{col 71}{space 4} .9767011{col 84}{space 3} 1.806176
{txt}{space 23}bush41 {c |}{col 31}{res}{space 2} .8050635{col 43}{space 2} .2403837{col 54}{space 1}   -0.73{col 63}{space 3}0.468{col 71}{space 4} .4484046{col 84}{space 3} 1.445407
{txt}{space 22}clinton {c |}{col 31}{res}{space 2} 2.323327{col 43}{space 2} 1.799763{col 54}{space 1}    1.09{col 63}{space 3}0.276{col 71}{space 4} .5090117{col 84}{space 3} 10.60457
{txt}{space 23}bush43 {c |}{col 31}{res}{space 2} 2.074806{col 43}{space 2} 1.045416{col 54}{space 1}    1.45{col 63}{space 3}0.147{col 71}{space 4} .7728399{col 84}{space 3} 5.570132
{txt}{space 24}_cons {c |}{col 31}{res}{space 2}  .009574{col 43}{space 2} .0092005{col 54}{space 1}   -4.84{col 63}{space 3}0.000{col 71}{space 4} .0014558{col 84}{space 3} .0629642
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 24}/ln_p {c |}{col 31}{res}{space 2} .1110492{col 43}{space 2} .0379194{col 54}{space 1}    2.93{col 63}{space 3}0.003{col 71}{space 4} .0367285{col 84}{space 3} .1853698
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                            p {c |}{col 31}{res}{space 2}  1.11745{col 43}{space 2}  .042373{col 71}{space 4} 1.037411{col 84}{space 3} 1.203663
{txt}                          1/p {c |}{col 31}{res}{space 2} .8948948{col 43}{space 2} .0339339{col 71}{space 4}  .830797{col 84}{space 3} .9639378
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimates store base1
{txt}
{com}. 
. 
. 
. *** NEED TO PRESENT THE INTERACTION COEFFICIENTS IN THE SAME RANGE-BASED INTERPRETATION AS DONE IN THE ASYMMETRIC LAPLACE REGRESSIONS: ///
> *** ONLY IT WILL TAKE ONLY ONE COMMAND LINE PER INTERACTION TERM: FOUR INTERACTION TERMS REPRESENTING H1-H4: ///
> 
. *** H1: filipresdistlewiszbtoplev2 * 0.401 ///
> *** H2: senpartydiffmedlewiszbtoplev2 * 0.118 ///
> *** H3: agencyindzbtoplev2 * 2.673 ///
> *** H4: zloyalmedianzbtoplev2 * 4.5765  ///
> 
. 
. *** GENERATE AVERAGE MARGINAL EFFECTS FROM ABOVE AND INSERT ON A SINGLE GRAPH *** 
. lincomest filipresdistlewiszbtoplev2  * 0.401
{txt}Confidence interval for formula:
{res}filipresdistlewiszbtoplev2*0.401

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.3553507{col 26}{space 2} .2224241{col 37}{space 1}   -1.60{col 46}{space 3}0.110{col 54}{space 4} -.791294{col 67}{space 3} .0805925
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store abs1
{txt}
{com}. *
. est restore base1
{txt}(results {stata estimates replay base1:base1} are active now)

{com}. lincomest senpartydiffmedlewiszbtoplev2 * 0.118
{txt}Confidence interval for formula:
{res}senpartydiffmedlewiszbtoplev2*0.118

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .5477028{col 26}{space 2}  .248973{col 37}{space 1}    2.20{col 46}{space 3}0.028{col 54}{space 4} .0597246{col 67}{space 3} 1.035681
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store sen1
{txt}
{com}. *
. est restore base1
{txt}(results {stata estimates replay base1:base1} are active now)

{com}. lincomest agencyindzbtoplev2 * 2.673
{txt}Confidence interval for formula:
{res}agencyindzbtoplev2*2.673

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0562685{col 26}{space 2} .3547754{col 37}{space 1}   -0.16{col 46}{space 3}0.874{col 54}{space 4}-.7516154{col 67}{space 3} .6390785
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store agen1
{txt}
{com}. *
. est restore base1
{txt}(results {stata estimates replay base1:base1} are active now)

{com}. lincomest zloyalmedianzbtoplev2 * 4.5765
{txt}Confidence interval for formula:
{res}zloyalmedianzbtoplev2*4.5765

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}    2.186{col 26}{space 2} .4567332{col 37}{space 1}    4.79{col 46}{space 3}0.000{col 54}{space 4}  1.29082{col 67}{space 3} 3.081181
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store zloy1
{txt}
{com}. *
. *
. coefplot abs1 sen1 agen1 zloy1, xline(0, lcolor(gs0) lpattern(dash)) ylabel(.7 "|President-Senate Filibuster Pivot|" .9 "Senate Party Polarization" 1.1 "Decision Maker Independence" 1.3 "Presidential Nominee Loyalty", labsize(medsmall)) msymbol(o) mcolor(black) msize(medium) ciopts(lcolor(black)) legend(off)
{res}{txt}
{com}. 
. graph save "Graph" "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB1.gph"
{res}{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB1.gph saved)

{com}. 
. graph export "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB1.eps"
{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB1.eps written in EPS format)

{com}. *added titles at .7 (Absolute Filibuster Distance), .9 (Senate Median), 1.1 (Agency Independence), 1.3 (Loyalty Median)
. 
. *
. *
. *
. *
. 
. 
. 
. *** MODEL B.2: ESTIMATES FOR INFORMATION VETTING CONFIRMATION DELAY [REPORTED OUT OF SENATE COMMITTEE DATE - NOMINATION DATE] USING WEIBULL PH REGRESSION ****
. drop _d _t _t0
{txt}
{com}. 
. ** STEP 1: ADD A CONSTANT OF 1 TO THE CONFIRMATION DURATION VARIABLE SO THAT IMMEDIATE CONFIRMATIONS ARE NOT CENSORED [CONFDURPLUS1 = confdur + 1] 
. gen legvetdurplus1 = legvetdur + 1
{txt}(249 missing values generated)

{com}. 
. ** STEP 2: SPECIFY NOMINATIONS THAT RESULT IN CONFIRMATIONS IN SAME CONGRESS [CONFIRMOBSERVED==0] AS 'FAILURES' WHEN SETTING THE DEPENDENT VARIABLE'S SURVIVAL FUNCTION **
. stset legvetdurplus1, failure(confirmobserved)

     {txt}failure event:  {res}confirmobserved != 0 & confirmobserved < .
{txt}obs. time interval:  {res}(0, legvetdurplus1]
{txt} exit on or before:  {res}failure

{txt}{hline 78}
{res}      1,345{txt}  total observations
{res}        249{txt}  event time missing (legvetdurplus1>=.)             PROBABLE ERROR
{hline 78}
{res}      1,096{txt}  observations remaining, representing
{res}      1,049{txt}  failures in single-record/single-failure data
{res}     63,446{txt}  total analysis time at risk and under observation
                                                at risk from t = {res}        0
                                     {txt}earliest observed entry t = {res}        0
                                          {txt}last observed exit t = {res}      702
{txt}
{com}. *
. ** STEP 3: ESTIMATE A WEIBULL HAZARD MODEL AND REPORT COEFFICIENTS IN HAZARD RATIO FORM **
. streg filipresdistancelewiszb filipresdistlewiszbtoplev2  senpartydiffmedianlewiszb senpartydiffmedlewiszbtoplev2  senworkload senhearing excalendarcong ///
> senmajagencyideoloppose senmajagencyideolalign agencyindzb  agencyindzbtoplev2  soucountagency1  presappnom endsession newpresterm fvatreated ///
> toplevel2 zloyalmedianzb zloyalmedianzbtoplev2 zmecompmedian zpecompmedian  gender minority admintermyr1  admintermyr2 admintermyr3 ///
> bush41 clinton bush43, distribution(weibull) vce(cluster sbagency) 

         {txt}failure _d:  {res}confirmobserved
   {txt}analysis time _t:  {res}legvetdurplus1

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-1703.4826
{txt}Iteration 1:   log pseudolikelihood = {res} -1687.268
{txt}Iteration 2:   log pseudolikelihood = {res}-1687.2677
{txt}Iteration 3:   log pseudolikelihood = {res}-1687.2677

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1687.2677}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1562.9312}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1515.8372}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1515.3025}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1515.3022}  
Iteration 5:{space 3}log pseudolikelihood = {res:-1515.3022}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}       1,013             {txt}Number of obs    =  {res}     1,013
{txt}No. of failures      = {res}         991
{txt}Time at risk         = {res}       57183
                                                {txt}Wald chi2({res}29{txt})    =  {res}    972.57
{txt}Log pseudolikelihood =   {res}-1515.3022             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 95:(Std. Err. adjusted for {res:50} clusters in sbagency)}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                           _t{col 31}{c |} Haz. Ratio{col 43}   Std. Err.{col 55}      z{col 63}   P>|z|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}filipresdistancelewiszb {c |}{col 31}{res}{space 2} 3.265123{col 43}{space 2} 5.204999{col 54}{space 1}    0.74{col 63}{space 3}0.458{col 71}{space 4} .1435429{col 84}{space 3} 74.27066
{txt}{space 3}filipresdistlewiszbtoplev2 {c |}{col 31}{res}{space 2} .4683637{col 43}{space 2} .2386006{col 54}{space 1}   -1.49{col 63}{space 3}0.137{col 71}{space 4} .1725647{col 84}{space 3} 1.271202
{txt}{space 4}senpartydiffmedianlewiszb {c |}{col 31}{res}{space 2} 1.38e-08{col 43}{space 2} 8.44e-08{col 54}{space 1}   -2.96{col 63}{space 3}0.003{col 71}{space 4} 8.47e-14{col 84}{space 3} .0022429
{txt}senpartydiffmedlewiszbtoplev2 {c |}{col 31}{res}{space 2} 52.79491{col 43}{space 2} 99.28068{col 54}{space 1}    2.11{col 63}{space 3}0.035{col 71}{space 4} 1.324066{col 84}{space 3} 2105.108
{txt}{space 18}senworkload {c |}{col 31}{res}{space 2} .9984495{col 43}{space 2}  .000626{col 54}{space 1}   -2.48{col 63}{space 3}0.013{col 71}{space 4} .9972233{col 84}{space 3} .9996771
{txt}{space 19}senhearing {c |}{col 31}{res}{space 2} 1.001013{col 43}{space 2} .0005469{col 54}{space 1}    1.85{col 63}{space 3}0.064{col 71}{space 4} .9999419{col 84}{space 3} 1.002086
{txt}{space 15}excalendarcong {c |}{col 31}{res}{space 2} 1.000031{col 43}{space 2} .0001029{col 54}{space 1}    0.30{col 63}{space 3}0.764{col 71}{space 4} .9998291{col 84}{space 3} 1.000233
{txt}{space 6}senmajagencyideoloppose {c |}{col 31}{res}{space 2} .9160738{col 43}{space 2} .1763576{col 54}{space 1}   -0.46{col 63}{space 3}0.649{col 71}{space 4} .6281476{col 84}{space 3} 1.335978
{txt}{space 7}senmajagencyideolalign {c |}{col 31}{res}{space 2} .9962476{col 43}{space 2} .1918526{col 54}{space 1}   -0.02{col 63}{space 3}0.984{col 71}{space 4} .6830414{col 84}{space 3} 1.453073
{txt}{space 18}agencyindzb {c |}{col 31}{res}{space 2} .8606662{col 43}{space 2} .0702223{col 54}{space 1}   -1.84{col 63}{space 3}0.066{col 71}{space 4}  .733474{col 84}{space 3} 1.009915
{txt}{space 11}agencyindzbtoplev2 {c |}{col 31}{res}{space 2} 1.074772{col 43}{space 2} .1299223{col 54}{space 1}    0.60{col 63}{space 3}0.551{col 71}{space 4} .8480469{col 84}{space 3} 1.362111
{txt}{space 14}soucountagency1 {c |}{col 31}{res}{space 2} 1.047131{col 43}{space 2} .0240756{col 54}{space 1}    2.00{col 63}{space 3}0.045{col 71}{space 4} 1.000991{col 84}{space 3} 1.095398
{txt}{space 19}presappnom {c |}{col 31}{res}{space 2} .9934469{col 43}{space 2} .0043664{col 54}{space 1}   -1.50{col 63}{space 3}0.135{col 71}{space 4} .9849257{col 84}{space 3} 1.002042
{txt}{space 19}endsession {c |}{col 31}{res}{space 2} .6156942{col 43}{space 2} .1442213{col 54}{space 1}   -2.07{col 63}{space 3}0.038{col 71}{space 4} .3890256{col 84}{space 3}  .974433
{txt}{space 18}newpresterm {c |}{col 31}{res}{space 2} 1.635636{col 43}{space 2} .1667801{col 54}{space 1}    4.83{col 63}{space 3}0.000{col 71}{space 4} 1.339346{col 84}{space 3} 1.997472
{txt}{space 19}fvatreated {c |}{col 31}{res}{space 2} 1.242669{col 43}{space 2} .1555541{col 54}{space 1}    1.74{col 63}{space 3}0.083{col 71}{space 4} .9723085{col 84}{space 3} 1.588205
{txt}{space 20}toplevel2 {c |}{col 31}{res}{space 2} .6300947{col 43}{space 2} .2009686{col 54}{space 1}   -1.45{col 63}{space 3}0.148{col 71}{space 4} .3372215{col 84}{space 3} 1.177325
{txt}{space 15}zloyalmedianzb {c |}{col 31}{res}{space 2} .8808214{col 43}{space 2} .0474818{col 54}{space 1}   -2.35{col 63}{space 3}0.019{col 71}{space 4} .7925063{col 84}{space 3} .9789782
{txt}{space 8}zloyalmedianzbtoplev2 {c |}{col 31}{res}{space 2} 1.564389{col 43}{space 2} .1482856{col 54}{space 1}    4.72{col 63}{space 3}0.000{col 71}{space 4} 1.299155{col 84}{space 3} 1.883773
{txt}{space 16}zmecompmedian {c |}{col 31}{res}{space 2} 1.032653{col 43}{space 2} .0596285{col 54}{space 1}    0.56{col 63}{space 3}0.578{col 71}{space 4} .9221537{col 84}{space 3} 1.156392
{txt}{space 16}zpecompmedian {c |}{col 31}{res}{space 2} .9152004{col 43}{space 2}   .04892{col 54}{space 1}   -1.66{col 63}{space 3}0.097{col 71}{space 4} .8241705{col 84}{space 3} 1.016284
{txt}{space 23}gender {c |}{col 31}{res}{space 2} 1.038028{col 43}{space 2} .0705009{col 54}{space 1}    0.55{col 63}{space 3}0.583{col 71}{space 4} .9086511{col 84}{space 3} 1.185826
{txt}{space 21}minority {c |}{col 31}{res}{space 2} .9045103{col 43}{space 2} .1024222{col 54}{space 1}   -0.89{col 63}{space 3}0.375{col 71}{space 4} .7244822{col 84}{space 3} 1.129274
{txt}{space 17}admintermyr1 {c |}{col 31}{res}{space 2} 1.468259{col 43}{space 2} .3608814{col 54}{space 1}    1.56{col 63}{space 3}0.118{col 71}{space 4} .9069573{col 84}{space 3} 2.376941
{txt}{space 17}admintermyr2 {c |}{col 31}{res}{space 2} 1.320931{col 43}{space 2} .3298066{col 54}{space 1}    1.11{col 63}{space 3}0.265{col 71}{space 4} .8097563{col 84}{space 3} 2.154795
{txt}{space 17}admintermyr3 {c |}{col 31}{res}{space 2} 1.128209{col 43}{space 2} .1724114{col 54}{space 1}    0.79{col 63}{space 3}0.430{col 71}{space 4} .8362003{col 84}{space 3} 1.522191
{txt}{space 23}bush41 {c |}{col 31}{res}{space 2} .9102512{col 43}{space 2} .2750621{col 54}{space 1}   -0.31{col 63}{space 3}0.756{col 71}{space 4} .5034345{col 84}{space 3} 1.645809
{txt}{space 22}clinton {c |}{col 31}{res}{space 2} 2.373255{col 43}{space 2}  1.84694{col 54}{space 1}    1.11{col 63}{space 3}0.267{col 71}{space 4} .5163136{col 84}{space 3} 10.90876
{txt}{space 23}bush43 {c |}{col 31}{res}{space 2} 2.250853{col 43}{space 2} 1.166897{col 54}{space 1}    1.56{col 63}{space 3}0.118{col 71}{space 4} .8148238{col 84}{space 3} 6.217713
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} .0149154{col 43}{space 2} .0142356{col 54}{space 1}   -4.41{col 63}{space 3}0.000{col 71}{space 4} .0022973{col 84}{space 3}  .096837
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 24}/ln_p {c |}{col 31}{res}{space 2} .0503664{col 43}{space 2} .0337227{col 54}{space 1}    1.49{col 63}{space 3}0.135{col 71}{space 4}-.0157289{col 84}{space 3} .1164618
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                            p {c |}{col 31}{res}{space 2} 1.051656{col 43}{space 2} .0354647{col 71}{space 4} .9843942{col 84}{space 3} 1.123515
{txt}                          1/p {c |}{col 31}{res}{space 2} .9508809{col 43}{space 2} .0320663{col 71}{space 4} .8900641{col 84}{space 3} 1.015853
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimates store base2
{txt}
{com}. 
. *** NEED TO PRESENT THE INTERACTION COEFFICIENTS IN THE SAME RANGE-BASED INTERPRETATION AS DONE IN THE ASYMMETRIC LAPLACE REGRESSIONS: ///
> *** ONLY IT WILL TAKE ONLY ONE COMMAND LINE PER INTERACTION TERM: FOUR INTERACTION TERMS REPRESENTING H1-H4: ///
> 
. *** H1: filipresdistlewiszbtoplev2 * 0.401 ///
> *** H2: senpartydiffmedlewiszbtoplev2 * 0.118 ///
> *** H3: agencyindzbtoplev2 * 2.673 ///
> *** H4: zloyalmedianzbtoplev2 * 4.5765  ///
> 
. 
. *** GENERATE AVERAGE MARGINAL EFFECTS FROM ABOVE AND INSERT ON A SINGLE GRAPH *** 
. lincomest filipresdistlewiszbtoplev2 * 0.401
{txt}Confidence interval for formula:
{res}filipresdistlewiszbtoplev2*0.401

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.3041625{col 26}{space 2} .2042832{col 37}{space 1}   -1.49{col 46}{space 3}0.137{col 54}{space 4}-.7045502{col 67}{space 3} .0962252
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store abs2
{txt}
{com}. *
. est restore base2
{txt}(results {stata estimates replay base2:base2} are active now)

{com}. lincomest senpartydiffmedlewiszbtoplev2 * 0.118
{txt}Confidence interval for formula:
{res}senpartydiffmedlewiszbtoplev2*0.118

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .4680369{col 26}{space 2} .2218987{col 37}{space 1}    2.11{col 46}{space 3}0.035{col 54}{space 4} .0331235{col 67}{space 3} .9029504
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store sen2
{txt}
{com}. *
. est restore base2
{txt}(results {stata estimates replay base2:base2} are active now)

{com}. lincomest agencyindzbtoplev2 * 2.673
{txt}Confidence interval for formula:
{res}agencyindzbtoplev2*2.673

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1927455{col 26}{space 2}  .323122{col 37}{space 1}    0.60{col 46}{space 3}0.551{col 54}{space 4} -.440562{col 67}{space 3} .8260531
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store agen2
{txt}
{com}. *
. est restore base2
{txt}(results {stata estimates replay base2:base2} are active now)

{com}. lincomest zloyalmedianzbtoplev2 * 4.5765
{txt}Confidence interval for formula:
{res}zloyalmedianzbtoplev2*4.5765

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} 2.047963{col 26}{space 2} .4337981{col 37}{space 1}    4.72{col 46}{space 3}0.000{col 54}{space 4} 1.197734{col 67}{space 3} 2.898191
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store zloy2
{txt}
{com}. *
. *
. coefplot abs2 sen2 agen2 zloy2, xline(0, lcolor(gs0) lpattern(dash)) ylabel(.7 "|President-Senate Filibuster Pivot|" .9 "Senate Party Polarization" 1.1 "Decision Maker Independence" 1.3 "Presidential Nominee Loyalty", labsize(medsmall)) msymbol(o) mcolor(black) msize(medium) ciopts(lcolor(black)) legend(off)
{res}{txt}
{com}. 
. graph save "Graph" "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB2.gph"
{res}{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB2.gph saved)

{com}. 
. graph export "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB2.eps"
{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB2.eps written in EPS format)

{com}. *added titles at .7 (Absolute Filibuster Distance), .9 (Senate Median), 1.1 (Agency Independence), 1.3 (Loyalty Median)
. 
. 
. *
. *
. *
. *
. *
. 
. 
. *** MODEL B.3: ESTIMATES FOR PROCEDURAL VETTING CONFIRMATION DELAY [CONFIRMATION DATE - REPORTED OUT OF SENATE COMMITTEE DATE] USING WEIBULL PH REGRESSION ****
. drop _d _t _t0
{txt}
{com}. 
. ** STEP 1: ADD A CONSTANT OF 1 TO THE CONFIRMATION DURATION VARIABLE SO THAT IMMEDIATE CONFIRMATIONS ARE NOT CENSORED [CONFDURPLUS1 = confdur + 1] 
. gen polvetdurplus1 = polvetdur + 1
{txt}(272 missing values generated)

{com}. 
. ** STEP 2: SPECIFY NOMINATIONS THAT RESULT IN CONFIRMATIONS IN SAME CONGRESS [CONFIRMOBSERVED==0] AS 'FAILURES' WHEN SETTING THE DEPENDENT VARIABLE'S SURVIVAL FUNCTION **
. stset polvetdurplus1, failure(confirmobserved)

     {txt}failure event:  {res}confirmobserved != 0 & confirmobserved < .
{txt}obs. time interval:  {res}(0, polvetdurplus1]
{txt} exit on or before:  {res}failure

{txt}{hline 78}
{res}      1,345{txt}  total observations
{res}        272{txt}  event time missing (polvetdurplus1>=.)             PROBABLE ERROR
{hline 78}
{res}      1,073{txt}  observations remaining, representing
{res}      1,049{txt}  failures in single-record/single-failure data
{res}     15,390{txt}  total analysis time at risk and under observation
                                                at risk from t = {res}        0
                                     {txt}earliest observed entry t = {res}        0
                                          {txt}last observed exit t = {res}      305
{txt}
{com}. *
. ** STEP 3: ESTIMATE A WEIBULL HAZARD MODEL AND REPORT COEFFICIENTS IN  HAZARD RATIO FORM **
. streg filipresdistancelewiszb filipresdistlewiszbtoplev2  senpartydiffmedianlewiszb senpartydiffmedlewiszbtoplev2  senworkload senhearing  excalendarcong ///
> senmajagencyideoloppose senmajagencyideolalign agencyindzb  agencyindzbtoplev2  soucountagency1  presappnom endsession newpresterm fvatreated ///
> toplevel2 zloyalmedianzb zloyalmedianzbtoplev2 zmecompmedian zpecompmedian  gender minority admintermyr1  admintermyr2 admintermyr3 ///
> bush41 clinton bush43, distribution(weibull) vce(cluster sbagency) 

         {txt}failure _d:  {res}confirmobserved
   {txt}analysis time _t:  {res}polvetdurplus1

{txt}Fitting constant-only model:

Iteration 0:   log pseudolikelihood = {res}-2117.8891
{txt}Iteration 1:   log pseudolikelihood = {res}-1886.0942
{txt}Iteration 2:   log pseudolikelihood = {res}-1885.9187
{txt}Iteration 3:   log pseudolikelihood = {res}-1885.9187

{txt}Fitting full model:
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1885.9187}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1759.9321}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1737.3394}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1737.2373}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1737.2372}  
{res}
{txt}Weibull PH regression

No. of subjects      = {res}       1,013             {txt}Number of obs    =  {res}     1,013
{txt}No. of failures      = {res}         991
{txt}Time at risk         = {res}       14345
                                                {txt}Wald chi2({res}29{txt})    =  {res}   1518.10
{txt}Log pseudolikelihood =   {res}-1737.2372             {txt}Prob > chi2      =  {res}    0.0000

{txt}{ralign 95:(Std. Err. adjusted for {res:50} clusters in sbagency)}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}                           _t{col 31}{c |} Haz. Ratio{col 43}   Std. Err.{col 55}      z{col 63}   P>|z|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}filipresdistancelewiszb {c |}{col 31}{res}{space 2} 76.62829{col 43}{space 2} 138.3498{col 54}{space 1}    2.40{col 63}{space 3}0.016{col 71}{space 4} 2.226246{col 84}{space 3} 2637.576
{txt}{space 3}filipresdistlewiszbtoplev2 {c |}{col 31}{res}{space 2} .3884672{col 43}{space 2} .2493677{col 54}{space 1}   -1.47{col 63}{space 3}0.141{col 71}{space 4} .1103938{col 84}{space 3} 1.366986
{txt}{space 4}senpartydiffmedianlewiszb {c |}{col 31}{res}{space 2} 4.79e-06{col 43}{space 2} .0000247{col 54}{space 1}   -2.37{col 63}{space 3}0.018{col 71}{space 4} 1.91e-10{col 84}{space 3} .1198262
{txt}senpartydiffmedlewiszbtoplev2 {c |}{col 31}{res}{space 2} 36.34663{col 43}{space 2} 88.08383{col 54}{space 1}    1.48{col 63}{space 3}0.138{col 71}{space 4} .3145062{col 84}{space 3} 4200.481
{txt}{space 18}senworkload {c |}{col 31}{res}{space 2} .9980714{col 43}{space 2}  .000499{col 54}{space 1}   -3.86{col 63}{space 3}0.000{col 71}{space 4} .9970939{col 84}{space 3} .9990498
{txt}{space 19}senhearing {c |}{col 31}{res}{space 2}   1.0024{col 43}{space 2} .0009005{col 54}{space 1}    2.67{col 63}{space 3}0.008{col 71}{space 4} 1.000636{col 84}{space 3} 1.004166
{txt}{space 15}excalendarcong {c |}{col 31}{res}{space 2} .9998173{col 43}{space 2} .0001184{col 54}{space 1}   -1.54{col 63}{space 3}0.123{col 71}{space 4} .9995853{col 84}{space 3} 1.000049
{txt}{space 6}senmajagencyideoloppose {c |}{col 31}{res}{space 2} 1.253615{col 43}{space 2} .1820468{col 54}{space 1}    1.56{col 63}{space 3}0.120{col 71}{space 4} .9430934{col 84}{space 3} 1.666378
{txt}{space 7}senmajagencyideolalign {c |}{col 31}{res}{space 2} 1.219587{col 43}{space 2} .1889714{col 54}{space 1}    1.28{col 63}{space 3}0.200{col 71}{space 4} .9001636{col 84}{space 3} 1.652357
{txt}{space 18}agencyindzb {c |}{col 31}{res}{space 2} .9047535{col 43}{space 2}  .078814{col 54}{space 1}   -1.15{col 63}{space 3}0.251{col 71}{space 4} .7627484{col 84}{space 3} 1.073197
{txt}{space 11}agencyindzbtoplev2 {c |}{col 31}{res}{space 2}  .802063{col 43}{space 2} .1055647{col 54}{space 1}   -1.68{col 63}{space 3}0.094{col 71}{space 4} .6196926{col 84}{space 3} 1.038103
{txt}{space 14}soucountagency1 {c |}{col 31}{res}{space 2} .9832172{col 43}{space 2} .0175742{col 54}{space 1}   -0.95{col 63}{space 3}0.344{col 71}{space 4} .9493687{col 84}{space 3} 1.018272
{txt}{space 19}presappnom {c |}{col 31}{res}{space 2} .9812234{col 43}{space 2} .0045534{col 54}{space 1}   -4.08{col 63}{space 3}0.000{col 71}{space 4} .9723394{col 84}{space 3} .9901886
{txt}{space 19}endsession {c |}{col 31}{res}{space 2} .9641038{col 43}{space 2} .1792008{col 54}{space 1}   -0.20{col 63}{space 3}0.844{col 71}{space 4} .6697434{col 84}{space 3} 1.387839
{txt}{space 18}newpresterm {c |}{col 31}{res}{space 2} 1.427012{col 43}{space 2} .2173694{col 54}{space 1}    2.33{col 63}{space 3}0.020{col 71}{space 4}  1.05869{col 84}{space 3} 1.923476
{txt}{space 19}fvatreated {c |}{col 31}{res}{space 2} .8376214{col 43}{space 2} .1647167{col 54}{space 1}   -0.90{col 63}{space 3}0.368{col 71}{space 4} .5697188{col 84}{space 3} 1.231502
{txt}{space 20}toplevel2 {c |}{col 31}{res}{space 2} .9877808{col 43}{space 2} .2378749{col 54}{space 1}   -0.05{col 63}{space 3}0.959{col 71}{space 4} .6161357{col 84}{space 3} 1.583597
{txt}{space 15}zloyalmedianzb {c |}{col 31}{res}{space 2} .9255003{col 43}{space 2} .0544072{col 54}{space 1}   -1.32{col 63}{space 3}0.188{col 71}{space 4} .8247782{col 84}{space 3} 1.038523
{txt}{space 8}zloyalmedianzbtoplev2 {c |}{col 31}{res}{space 2} 1.274294{col 43}{space 2} .0972816{col 54}{space 1}    3.18{col 63}{space 3}0.001{col 71}{space 4} 1.097205{col 84}{space 3} 1.479966
{txt}{space 16}zmecompmedian {c |}{col 31}{res}{space 2} .8909797{col 43}{space 2} .0410208{col 54}{space 1}   -2.51{col 63}{space 3}0.012{col 71}{space 4} .8141012{col 84}{space 3}  .975118
{txt}{space 16}zpecompmedian {c |}{col 31}{res}{space 2} 1.078008{col 43}{space 2} .0646524{col 54}{space 1}    1.25{col 63}{space 3}0.210{col 71}{space 4} .9584556{col 84}{space 3} 1.212472
{txt}{space 23}gender {c |}{col 31}{res}{space 2} 1.031944{col 43}{space 2} .1285573{col 54}{space 1}    0.25{col 63}{space 3}0.801{col 71}{space 4} .8083793{col 84}{space 3} 1.317337
{txt}{space 21}minority {c |}{col 31}{res}{space 2}  1.16252{col 43}{space 2} .1211797{col 54}{space 1}    1.44{col 63}{space 3}0.149{col 71}{space 4} .9477024{col 84}{space 3} 1.426029
{txt}{space 17}admintermyr1 {c |}{col 31}{res}{space 2} 1.919479{col 43}{space 2} .3270075{col 54}{space 1}    3.83{col 63}{space 3}0.000{col 71}{space 4} 1.374582{col 84}{space 3}  2.68038
{txt}{space 17}admintermyr2 {c |}{col 31}{res}{space 2} 1.921685{col 43}{space 2} .3407659{col 54}{space 1}    3.68{col 63}{space 3}0.000{col 71}{space 4} 1.357505{col 84}{space 3} 2.720338
{txt}{space 17}admintermyr3 {c |}{col 31}{res}{space 2}  1.82043{col 43}{space 2} .2629457{col 54}{space 1}    4.15{col 63}{space 3}0.000{col 71}{space 4} 1.371592{col 84}{space 3} 2.416144
{txt}{space 23}bush41 {c |}{col 31}{res}{space 2} .9460466{col 43}{space 2} .2588243{col 54}{space 1}   -0.20{col 63}{space 3}0.839{col 71}{space 4} .5533966{col 84}{space 3} 1.617293
{txt}{space 22}clinton {c |}{col 31}{res}{space 2} 2.228956{col 43}{space 2} 1.496982{col 54}{space 1}    1.19{col 63}{space 3}0.233{col 71}{space 4} .5976252{col 84}{space 3} 8.313313
{txt}{space 23}bush43 {c |}{col 31}{res}{space 2} 1.258838{col 43}{space 2} .5397244{col 54}{space 1}    0.54{col 63}{space 3}0.591{col 71}{space 4} .5432741{col 84}{space 3} 2.916896
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} .0754695{col 43}{space 2} .0866104{col 54}{space 1}   -2.25{col 63}{space 3}0.024{col 71}{space 4}   .00796{col 84}{space 3} .7155303
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 24}/ln_p {c |}{col 31}{res}{space 2}-.2465397{col 43}{space 2} .0399482{col 54}{space 1}   -6.17{col 63}{space 3}0.000{col 71}{space 4}-.3248367{col 84}{space 3}-.1682427
{txt}{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                            p {c |}{col 31}{res}{space 2} .7815003{col 43}{space 2} .0312195{col 71}{space 4} .7226453{col 84}{space 3} .8451487
{txt}                          1/p {c |}{col 31}{res}{space 2}  1.27959{col 43}{space 2} .0511173{col 71}{space 4} 1.183224{col 84}{space 3} 1.383805
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{p 0 6 2}Note: {res:_cons} estimates baseline hazard{txt}.{p_end}

{com}. 
. estimates store base3
{txt}
{com}. 
. *** NEED TO PRESENT THE INTERACTION COEFFICIENTS IN THE SAME RANGE-BASED INTERPRETATION AS DONE IN THE ASYMMETRIC LAPLACE REGRESSIONS: ///
> *** ONLY IT WILL TAKE ONLY ONE COMMAND LINE PER INTERACTION TERM: FOUR INTERACTION TERMS REPRESENTING H1-H4: ///
> 
. *** H1: filipresdistlewiszbtoplev2 * 0.401 ///
> *** H2: senpartydiffmedlewiszbtoplev2 * 0.118 ///
> *** H3: agencyindzbtoplev2 * 2.673 ///
> *** H4: zloyalmedianzbtoplev2 * 4.5765  ///
> 
. 
. *** GENERATE AVERAGE MARGINAL EFFECTS FROM ABOVE AND INSERT ON A SINGLE GRAPH *** 
. lincomest filipresdistlewiszbtoplev2 * 0.401
{txt}Confidence interval for formula:
{res}filipresdistlewiszbtoplev2*0.401

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.3791641{col 26}{space 2} .2574129{col 37}{space 1}   -1.47{col 46}{space 3}0.141{col 54}{space 4}-.8836841{col 67}{space 3} .1253558
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store abs3
{txt}
{com}. *
. est restore base3
{txt}(results {stata estimates replay base3:base3} are active now)

{com}. lincomest senpartydiffmedlewiszbtoplev2 * 0.118
{txt}Confidence interval for formula:
{res}senpartydiffmedlewiszbtoplev2*0.118

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .423986{col 26}{space 2} .2859658{col 37}{space 1}    1.48{col 46}{space 3}0.138{col 54}{space 4}-.1364967{col 67}{space 3} .9844686
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store sen3
{txt}
{com}. *
. est restore base3
{txt}(results {stata estimates replay base3:base3} are active now)

{com}. lincomest agencyindzbtoplev2 * 2.673
{txt}Confidence interval for formula:
{res}agencyindzbtoplev2*2.673

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.5895787{col 26}{space 2} .3518108{col 37}{space 1}   -1.68{col 46}{space 3}0.094{col 54}{space 4}-1.279115{col 67}{space 3} .0999579
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store agen3
{txt}
{com}. *
. est restore base3
{txt}(results {stata estimates replay base3:base3} are active now)

{com}. lincomest zloyalmedianzbtoplev2 * 4.5765
{txt}Confidence interval for formula:
{res}zloyalmedianzbtoplev2*4.5765

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}          _t{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  1.10931{col 26}{space 2}  .349377{col 37}{space 1}    3.18{col 46}{space 3}0.001{col 54}{space 4} .4245432{col 67}{space 3} 1.794076
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. est store zloy3
{txt}
{com}. *
. *
. coefplot abs3 sen3 agen3 zloy3, xline(0, lcolor(gs0) lpattern(dash)) ylabel(.7 "|President-Senate Filibuster Pivot|" .9 "Senate Party Polarization" 1.1 "Decision Maker Independence" 1.3 "Presidential Nominee Loyalty", labsize(medsmall)) msymbol(o) mcolor(black) msize(medium) ciopts(lcolor(black)) legend(off)
{res}{txt}
{com}. 
. graph save "Graph" "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB3.gph"
{res}{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/Appendix B/FigureB3.gph saved)

{com}. 
. graph export "/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB3.eps"
{txt}(file /Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Graphics/EPS/Appendix B/FigureB3.eps written in EPS format)

{com}. *added titles at .7 (Absolute Filibuster Distance), .9 (Senate Median), 1.1 (Agency Independence), 1.3 (Loyalty Median)
. 
. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/JAYBYERS/Dropbox/Jason Byers/Co-Authored Projects/Projects with Krause/Krause Projects/Confirmation Dynamics Project/Nominee Characteristics Project/JOPDRMJB/Output/APPENDIX B MODELS.04-20-2021.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}22 Apr 2021, 21:09:00
{txt}{.-}
{smcl}
{txt}{sf}{ul off}